Senior Director, AI Deployment

Role Overview

Omnicom is seeking a highly technical, client-oriented Senior Director, AI Deployment to lead the implementation and scaling of AI-enabled solutions across our healthcare agencies and clients. This role sits at the intersection of AI, technology, data, creative, and client delivery. The Senior Director will translate business and client needs into practical AI solutions, architectures, workflows, and implementation plans, helping move AI initiatives from prototype through production and adoption.

Working within a highly matrixed organization, this individual will partner across multiple Omnicom Health agencies and capabilities, bringing together the right technical, strategic, creative, data, and client expertise for each engagement. The role will also help establish deployment standards and governance that align with the broader Omnicom operating model, healthcare-industry requirements, and individual client policies and technology environments.

Key Responsibilities

AI Deployment & Technical Leadership

• Lead end-to-end deployment of generative AI, agentic AI, machine learning, advanced analytics, and AI-enabled workflows from discovery and prototype through production.
• Translate business and client requirements into solution architectures, implementation roadmaps, integration requirements, and operating models.
• Guide the deployment of AI agents, copilots, knowledge systems, decision-support tools, and workflow automation.
• Provide hands-on technical leadership across architecture reviews, model evaluation, integrations, testing, troubleshooting, and production readiness.
• Partner with foundational platform, engineering, data, security, and infrastructure teams to leverage shared capabilities and accelerate deployment.
• Develop reusable architectures, components, playbooks, and deployment approaches that can scale across agencies and clients.

Omnicom & Cross-Agency Collaboration

• Work across multiple Omnicom agencies and capabilities to deploy AI solutions that address shared and agency-specific business needs.
• Navigate a highly matrixed organization, coordinating teams across technology, data, strategy, creative, analytics, product, operations, account management, and client leadership.
• Balance enterprise standards and reusable capabilities with the distinct needs of individual agencies, brands, and client organizations.
• Help create repeatable deployment models that enable agencies to adopt and operationalize AI without duplicating capabilities unnecessarily.
• Build strong working relationships with agency and enterprise leaders to identify dependencies, resolve challenges, and accelerate adoption.

Governance, Compliance & Responsible AI

• Translate Omnicom AI governance, security, privacy, and technology standards into practical requirements for individual deployments.
• Work with legal, privacy, security, compliance, medical/regulatory, and technology stakeholders to establish appropriate governance throughout the solution lifecycle.
• Adapt implementation and governance approaches to the requirements of healthcare and pharmaceutical clients, including regulated data, content, workflows, and medical/legal/regulatory considerations.
• Reconcile Omnicom standards with individual client requirements, technology environments, policies, and risk tolerances.
• Establish appropriate evaluation, testing, documentation, monitoring, human oversight, and escalation processes for deployed AI solutions.

Client & Delivery Leadership

• Serve as a senior technical and delivery partner to clients, translating complex AI concepts and technical trade-offs into clear business terms.
• Lead discovery sessions, solution workshops, technical reviews, implementation planning, and deployment workstreams.
• Coordinate multidisciplinary teams including solution architects, engineers, data scientists, creative technologists, product teams, and delivery leads.
• Manage dependencies, risks, resources, and priorities across concurrent AI initiatives.
• Define success measures and ensure deployments are designed around adoption and measurable business impact, not simply technical implementation.
• Support business development by assessing opportunities, shaping solutions, and defining realistic scopes, resource needs, and deployment approaches.

Qualifications

• 7+ years of experience across AI engineering, software engineering, data science, machine learning, solution architecture, technical consulting, or related disciplines.
• 3+ years leading complex technology implementations or multidisciplinary technical teams.
• Demonstrated experience moving AI or machine learning solutions from prototype into production.
• Strong working knowledge of generative AI and LLMs, agentic architectures, RAG, knowledge systems, APIs and integrations, cloud architectures, MLOps, data engineering, and AI evaluation.
• Experience with Azure, AWS, Google Cloud, or multi-cloud environments.
• Strong technical proficiency with Python and modern software development practices.
• Experience operating within complex, matrixed organizations and influencing teams without direct reporting authority.
• Strong client-facing, stakeholder-management, problem-solving, and communication skills.

Preferred Experience

• Pharmaceutical, biotechnology, healthcare, or life sciences experience.
• Experience deploying technology within regulated or highly governed environments.
• Familiarity with healthcare data, privacy, medical/legal/regulatory review, and responsible AI considerations.
• Experience with healthcare marketing, commercial strategy, omnichannel engagement, content operations, personalization, or customer experience.
• Consulting, professional services, agency, systems integration, or forward-deployment experience.
• Experience scaling AI capabilities across multiple business units, agencies, brands, or clients.